Retrospective correction of the heel effect in hand radiographs

Behiels, Gert; Maes, Frederik; Vandermeulen, Dirk; Suetens, Paul

doi:10.1016/s1361-8415(02)00078-6

Cited by 19 publications

(9 citation statements)

References 9 publications

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“…A further random sampling was made from each set, to obtain exactly the same number (500) of profiles for each class. To remove any effects (such as the anode heel-effect [49]) due to different numbers of profiles from left and right breasts, each profile was used twice -once as sampled and once with the sample values in reverse order. This scheme allowed separate data to be used for PCA modeling, training the classifier, and testing the classifier.…”

Section: F Evaluation Methodology 1) Detection Performancementioning

confidence: 99%

Linear Structures in Mammographic Images: Detection and Classification

Zwiggelaar

Astley

Boggis

et al. 2004

IEEE Trans. Med. Imaging

129

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We describe methods for detecting linear structures in mammograms, and for classifying them into anatomical types (vessels, spicules, ducts, etc). Several different detection methods are compared, using realistic synthetic images and receiver operating characteristic (ROC) analysis. There are significant differences (p < 0.001) between the methods, with the best giving an Az value for pixel-level detection of 0.943. We also investigate methods for classifying the detected linear structures into anatomical types, using their cross-sectional profiles, with particular emphasis on recognising the "spicules" and "ducts" associated with some of the more subtle abnormalities. Automatic classification results are compared with expert annotations using ROC analysis, demonstrating useful discrimination between anatomical classes (Az = 0.746). Some of this discrimination relies on simple attributes such as profile width and contrast, but important information is also carried by the shape of the profile (Az = 0.653). The methods presented have potentially wide application in improving the specificity of abnormality detection by exploiting additional anatomical information.

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Section: F Evaluation Methodology 1) Detection Performancementioning

confidence: 99%

Linear Structures in Mammographic Images: Detection and Classification

Zwiggelaar

Astley

Boggis

et al. 2004

IEEE Trans. Med. Imaging

129

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“…A computational method based on heel effect modeling and image partitioning was proposed in Ref. 6. Direct exposure areas in an uncorrected image were segmented out.…”

Section: Introductionmentioning

confidence: 99%

“…The method was tested in correcting images of extremity examinations, but had limited applications in chest radiographs since they rarely contain direct radiation regions. This heel effect model 6 was generalized to a 2D model with a continuous spectral beam taken into account. 7 The structural and material information about the anode were regarded as known parameters and used in the model formula to generate a simulated heel pattern.…”

Section: Introductionmentioning

confidence: 99%

Heel effect adaptive flat field correction of digital x-ray detectors

Wang

2013

Med. Phys.

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The Duo-SID correction method has substantially improved on conventional offset/gain corrections for digital x-ray imaging in an SID-variant environment. The technique is relatively simple, and can be easily incorporated into multiple-point gain calibration/correction techniques. It offers a potentially valuable tool for preprocessing digital x-ray images to boost image quality of mammography, chest and cardiac radiography, as well as automated computer aided diagnostic radiology.

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“…Esse processo permitiu verificar a porcentagem de variação eliminada e a escala dinâmica dos pixels da região de fundo (BEHIELS et al, 2002) .…”

Section: 5-testes Dos Algoritmosunclassified

Método computacional automático para correção do efeito \"heel\" nas imagens radiográficas

Nascimento¹

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Retrospective correction of the heel effect in hand radiographs

Cited by 19 publications

References 9 publications

Linear Structures in Mammographic Images: Detection and Classification

Linear Structures in Mammographic Images: Detection and Classification

Heel effect adaptive flat field correction of digital x-ray detectors

Método computacional automático para correção do efeito \"heel\" nas imagens radiográficas

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